Instructions to use syssec-utd/py314-pylingual-v7-segmenter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syssec-utd/py314-pylingual-v7-segmenter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="syssec-utd/py314-pylingual-v7-segmenter")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("syssec-utd/py314-pylingual-v7-segmenter") model = AutoModelForTokenClassification.from_pretrained("syssec-utd/py314-pylingual-v7-segmenter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f6fc506084b938ce38f7267e9fc154be2c8374952dd3deb916ce7e67b90417d
- Size of remote file:
- 5.27 kB
- SHA256:
- b120c0c75f644f0ba7748caf86c27e3c62c36e1b5b3368e5138c7e9bdd9bf7dd
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